[HTML][HTML] Applications of machine learning methods for engineering risk assessment–A review
The purpose of this article is to present a structured review of publications utilizing machine
learning methods to aid in engineering risk assessment. A keyword search is performed to …
learning methods to aid in engineering risk assessment. A keyword search is performed to …
[HTML][HTML] Machine learning applied to road safety modeling: A systematic literature review
Road safety modeling is a valuable strategy for promoting safe mobility, enabling the
development of crash prediction models (CPM) and the investigation of factors contributing …
development of crash prediction models (CPM) and the investigation of factors contributing …
Predicting multiple types of traffic accident severity with explanations: A multi-task deep learning framework
Z Yang, W Zhang, J Feng - Safety science, 2022 - Elsevier
Predicting traffic accident severity is essential for traffic accident prevention and vulnerable
road user safety. Furthermore, the explainability of the prediction is crucial for practitioners to …
road user safety. Furthermore, the explainability of the prediction is crucial for practitioners to …
[HTML][HTML] Evaluating expressway traffic crash severity by using logistic regression and explainable & supervised machine learning classifiers
The number of expressway road accidents in Sri Lanka has significantly increased (by 20%)
due to the expansion of the transport network and high traffic volume. It is crucial to identify …
due to the expansion of the transport network and high traffic volume. It is crucial to identify …
A data mining approach to characterize road accident locations
Data mining has been proven as a reliable technique to analyze road accidents and provide
productive results. Most of the road accident data analysis use data mining techniques …
productive results. Most of the road accident data analysis use data mining techniques …
Comparing machine learning and deep learning methods for real-time crash prediction
A Theofilatos, C Chen… - Transportation research …, 2019 - journals.sagepub.com
Although there are numerous studies examining the impact of real-time traffic and weather
parameters on crash occurrence on freeways, to the best of the authors' knowledge there …
parameters on crash occurrence on freeways, to the best of the authors' knowledge there …
Construction safety predictions with multi-head attention graph and sparse accident networks
The reliability of risk assessment is crucial for designing effective construction safety
management strategies. Construction safety prediction using machine learning models is …
management strategies. Construction safety prediction using machine learning models is …
Applications of machine learning methods in traffic crash severity modelling: current status and future directions
As a key area of traffic safety research, crash severity modelling has attracted tremendous
attention. Recently, there has been growing interest in applying machine learning (ML) …
attention. Recently, there has been growing interest in applying machine learning (ML) …
A real-time crash prediction fusion framework: An imbalance-aware strategy for collision avoidance systems
Real-time traffic crash prediction has been a major concern in the development of Collision
Avoidance Systems (CASs) along with other intelligent and resilient transportation …
Avoidance Systems (CASs) along with other intelligent and resilient transportation …
Review of medical decision support and machine-learning methods
A Awaysheh, J Wilcke, F Elvinger, L Rees… - Veterinary …, 2019 - journals.sagepub.com
Machine-learning methods can assist with the medical decision-making processes at the
both the clinical and diagnostic levels. In this article, we first review historical milestones and …
both the clinical and diagnostic levels. In this article, we first review historical milestones and …